Runit (CEO Seo Beom-seok) announced that it will present 21 of its latest research results at the '2026 European Congress of Radiology (ECR 2026)' held in Vienna, Austria from March 4th to 8th.
This conference will present clinical evaluation studies of Lunit's mammography AI analysis solution, "Lunit Insight MMG," breast density quantification solution, "Scorecard," and chest X-ray AI analysis solution, "Lunit Insight CXR." Of the 21 studies, 13 will be presented orally, and eight will be presented as posters.
One of the key studies was a study on early breast cancer risk assessment conducted by the AULSS n.2 'Marca Trevigiana', a health institution in the Treviso region of Italy. After analyzing mammography data from 67,686 women, they found that the Lunit Insight MMG-based risk score (ExRS) was useful in identifying cases with a high risk of developing breast cancer later among women who had a normal result at the first screening. The average score of 451 women who were actually diagnosed with breast cancer increased from 15.4 points at the first screening to 73.9 points at the second screening, while the scores of 67,235 people who tested negative both times did not change significantly.
Another study, conducted by a research team at the University of Nottingham in the UK, evaluated the potential use of AI in the NHSBSP interval cancer identification process. An analysis of 409 interval cancer cases revealed that AI scoring could help prioritize Category 1 cases, which account for the majority, and identify cases requiring closer review by experts.
Results from a large-scale randomized controlled trial (RCT) utilizing Lunit International's breast density quantification solution, "Scorecard," will also be released. A research team at Utrecht University Hospital in the Netherlands performed additional MRI screening on women classified as having extremely dense breasts. The results showed a significantly lower incidence of advanced breast cancer at the third screening compared to the control group. This study suggests that quantitative breast density assessment can accurately identify high-risk women and guide them toward additional screening.
Seo Beom-seok, CEO of Lunit, said, “These studies demonstrate that AI can contribute to early risk assessment, screening quality management, and high-risk group screening beyond interpretation support. We will continue to accumulate clinical evidence based on collaboration with global medical institutions.”
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